Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

What are the best routes to effectively model human colorectal cancer?

Young, Madeleine, Ordonez, Liliana and Clarke, Alan Richard 2013. What are the best routes to effectively model human colorectal cancer? Molecular Oncology 7 (2) , pp. 178-189. 10.1016/j.molonc.2013.02.006

Full text not available from this repository.


Colorectal cancer (CRC) is the third most common cancer in the UK, with over 37,500 people being diagnosed every year. Survival rates for CRC have doubled in the last 30 years and it is now curable if diagnosed early, but still over half of all sufferers do not survive for longer than 5 years after diagnosis. The major complication to treating this disease is that of metastasis, specifically to the liver, which is associated with a 5 year survival of less than 5%. These statistics highlight the importance of the development of earlier detection techniques and more targeted therapeutics. The future of treating this disease therefore lies in increasing understanding of the mutations which cause tumourigenesis, and insight into the development and progression of this complex disease. This can only be achieved through the use of functional models which recapitulate all aspects of the human disease. There is a wide range of models of CRC available to researchers, but all have their own strengths and weaknesses. Here we review how CRC can be modelled and discuss the future of modelling this complex disease, with a particular focus on how genetically engineered mouse models have revolutionised this area of research.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Biosciences
European Cancer Stem Cell Research Institute (ECSCRI)
Subjects: R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Uncontrolled Keywords: Colorectal cancer; Mouse models; Genetic modification
Publisher: Elsevier
ISSN: 1574-7891
Last Modified: 07 Jan 2022 02:39

Citation Data

Cited 32 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item